TY - JOUR
T1 - Biological brain age prediction using machine learning on structural neuroimaging data
T2 - Multi-cohort validation against biomarkers of Alzheimer’s disease and neurodegeneration stratified by sex
AU - Mayoral, Irene Cumplido
AU - García-Prat, Marina
AU - Operto, Grégory
AU - Falcon, Carles
AU - Shekari, Mahnaz
AU - Cacciaglia, Raffaele
AU - Milà-Alomà, Marta
AU - Lorenzini, Luigi
AU - Ingala, Silvia
AU - Wink, Alle Meije
AU - Mutsaerts, Henk Jmm
AU - Minguillón, Carolina
AU - Fauria, Karine
AU - Molinuevo, José Luis
AU - Haller, Sven
AU - Chetelat, Gael
AU - OASIS study
AU - Waldman, Adam
AU - Schwarz, Adam
AU - Barkhof, Frederik
AU - Suridjan, Ivonne
AU - Kollmorgen, Gwendlyn
AU - Bayfield, Anna
AU - ALFA Study
AU - Zetterberg, Henrik
AU - Blennow, Kaj
AU - EPAD study
AU - Suárez-Calvet, Marc
AU - ADNI study
AU - Vilaplana, Verónica
AU - Gispert, Juan Domingo
N1 - Funding Information: The project leading to these results has received funding from “la Caixa” Foundation (ID 100010434), under agreement LCF/PR/GN17/50300004 and the Alzheimer’s Association and an international anonymous charity foundation through the TriBEKa Imaging Platform project (TriBEKa-17-519007). Additional support has been received from the Universities and Research Secretariat, Ministry of Business and Knowledge of the Catalan Government under the grant no. 2017-SGR-892 and the Spanish Research Agency (AEI) under project PID2020-116907RB-I00 of the call MCIN/ AEI /10.13039/501100011033. FB is supported by the NIHR biomedical research center at UCLH. MSC receives funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (Grant agreement No. 948677), the Instituto de Salud Carlos III (PI19/00155), and from a fellowship from ”la Caixa” Foundation (ID 100010434) and from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 847648 (LCF/BQ/PR21/11840004). Publisher Copyright: 2023.
PY - 2023/4/1
Y1 - 2023/4/1
N2 - Brain-age can be inferred from structural neuroimaging and compared to chronological age (brain-age delta) as a marker of biological brain aging. Accelerated aging has been found in neurodegenerative disorders like Alzheimer’s disease (AD), but its validation against markers of neurodegeneration and AD is lacking. Here, imaging-derived measures from the UK Biobank dataset (N=22,661) were used to predict brain-age in 2,314 cognitively unimpaired (CU) individuals at higher risk of AD and mild cognitive impaired (MCI) patients from four independent cohorts with available biomarker data: ALFA+, ADNI, EPAD and OASIS. Brain-age delta was associated with abnormal amyloid-β, more advanced stages (AT) of AD pathology and APOE-ε4 status. Brain age delta was positively associated with plasma neurofilament light, a marker of neurodegeneration, and sex differences in the brain effects of this marker were found. These results validate brain-age delta as a non-invasive marker of biological brain aging in non-demented individuals with abnormal levels of biomarkers of AD and axonal injury.
AB - Brain-age can be inferred from structural neuroimaging and compared to chronological age (brain-age delta) as a marker of biological brain aging. Accelerated aging has been found in neurodegenerative disorders like Alzheimer’s disease (AD), but its validation against markers of neurodegeneration and AD is lacking. Here, imaging-derived measures from the UK Biobank dataset (N=22,661) were used to predict brain-age in 2,314 cognitively unimpaired (CU) individuals at higher risk of AD and mild cognitive impaired (MCI) patients from four independent cohorts with available biomarker data: ALFA+, ADNI, EPAD and OASIS. Brain-age delta was associated with abnormal amyloid-β, more advanced stages (AT) of AD pathology and APOE-ε4 status. Brain age delta was positively associated with plasma neurofilament light, a marker of neurodegeneration, and sex differences in the brain effects of this marker were found. These results validate brain-age delta as a non-invasive marker of biological brain aging in non-demented individuals with abnormal levels of biomarkers of AD and axonal injury.
UR - http://www.scopus.com/inward/record.url?scp=85162933801&partnerID=8YFLogxK
U2 - https://doi.org/10.7554/eLife.81067
DO - https://doi.org/10.7554/eLife.81067
M3 - Article
C2 - 37067031
SN - 2050-084X
VL - 12
JO - eLife
JF - eLife
M1 - e81067
ER -